Pseudo bond graph model of thermal transfers sustained by ice quantity of a domestic refrigerator for energy saving application
Bibliographic record
Abstract
This paper presents a study on the use of ice to improve the energy efficiency of a domestic refrigerator by applying a pseudo bond graph model that describes the thermal transfers sustained by a quantity of ice introduced inside the cavity of refrigeration. The use of ice resulted in a global energy saving of 4.68%. The effect of ice was found to be more significant during the transitional regime. It reduced the response time to reach the stable average temperature from 15 h to only 3.5 h compared to when not using ice. This achievement did not cost additional electrical power, but rather allowed a saving of electrical energy of 76.73%. However, during the steady state, a reduction in the energy efficiency was noted. An improvement in the cooling by keeping the temperature inside the refrigerator more homogeneous is also proved. The model has two inputs: the outside temperature, and the modulated temperature of the evaporator. This latter determines the functioning of the compressor cycle. The model describes the thermal transfers by natural convection inside the refrigerator. Two experiments were carried out to make a performance comparison and to prove the influence of ice in cooling and energy saving. We used real measurements to modulate the evaporator temperature source in the pseudo bond graph model. The simulation results show the effectiveness of the proposed approach. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".